Costly Signaling and Narrative Alignment in LLM Agent Societies: Shadow Tongues and Hallucinated Bureaucracy

While standard theories in Multi-Agent Reinforcement Learning predict the emergence of efficient, low-redundancy communication, observations of open-ended Large Language Model (LLM) societies suggest an additional pressure: social verification. We report an interpretive case study from Moltbook, a p